Abstract
This review considers casual inference in observational studies which can prove medical treatment. The main aim of this study is to describe about its application in non-randomized clinical studies and in persons who support regulatory applications for marketing medical product. Propensity score makes an easy study about the large number of groups which cannot be randomized. By measuring the covariates, the methods which are used to measure the propensity score mimic the covariates. This study shows an illustration of the steps in the study and construction of propensity scores verses normal treatment of seriously ill individuals. Propensity score has the major advantage over alternate approaches when the treatment methods of illness do not overlap.
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